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测绘学报  2014 

矢量数据变化对象的快速定位与最优组合匹配方法

DOI: 10.13485/j.cnki.11-2089.2014.0191, PP. 1285-1292

Keywords: 变化信息,格网划分,语义树,最优组合匹配

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Abstract:

要素变化信息对地物生命周期的记录、时空数据库的构建、GIS数据库的更新有重要意义.针对大数据量的变化信息发现,本文采用基于格网划分的方法,通过对空间特征与属性特征汇总信息的对比,只对发生变化的格网进行检测,缩小了检测范围与空间查询区域.为解决要素变化前后的匹配问题,提出一种最优组合匹配法,通过对组合对象空间特征及语义特征的综合比较,从候选要素中选取最佳匹配对象.试验证明,该方法能够高效准确地实现大数据量的矢量数据变化信息的探测,并能很好地解决非一对一的要素匹配问题.

References

[1]  WU Jianhua. Entity Matching Methods Based on Combining Multi-similarity-characteristics Considering Environment Similarity[J]. Geography and Geo-Information Science, 2010, 26(4): 1-6. (吴建华. 顾及环境相似的多特征组合实体匹配方法[J]. 地理与地理信息科学, 2010, 26(4): 1-6.)
[2]  XU Junkui, WU Fang, WEI Huifeng. Areal Settlements Matching Algorithm Based on Artificial Neural Network Technique[J]. Journal of Geomatics Science and Technology, 2013, 30(3): 293-298. (许俊奎,武芳, 魏慧峰. 人工神经网络在居民地面状匹配中的应用[J]. 测绘科学技术学报, 2013, 30(3): 293-298.)
[3]  CHEN Yumin, GONG Jianya, SHI Wenzhong. A Distance-based Matching Algorithm for Multi-scale Road Networks[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(1): 84-90. (陈玉敏,龚健雅,史文中. 多尺度道路网的距离匹配算法研究[J]. 测绘学报, 2007, 36(1): 84-90.)
[4]  GUO Taisheng, ZHANG Xinchang, LIANG Zhiyu. Research on Change Information Recongition Method of Vector Data Based on Neural Network Decision Tree[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(6): 937-944.(郭泰圣,张新长,梁志宇. 神经网络决策树的矢量数据变化信息快速识别方法[J]. 测绘学报,2013, 42(6): 937-944.)
[5]  COBB M A, CHUNG M J, FOLEY I H, et al. A Rule-based Approach for the Conation of Attributed Vector Data[J]. GeoInformatica, 1998, 2(1): 7-35.
[6]  DIAO Xingchun, TAN Mingchao, CAO Jianjun. New Method of Character String Similarity Computing Based on Fusing Multiple Edit Distances[J]. Application Research of Computers, 2010, 27(12): 4523-4525. (刁兴春,谭明超,曹建军. 一种融合多种编辑距离的字符串相似度计算方法[J]. 计算机应用研究, 2010, 27(12): 4523-4525.)
[7]  HASTINGS J T. Automated Conflation of Digital Gazetteer Data[J]. International Journal of Geographical Information Science, 2008, 22(10): 1109-1127.
[8]  LOPEZ-PELLICER F J, LACASTA J, FLORCZYK A, et al. An Ontology for the Representation of Spatiotemporal Jurisdictional Domains in Information Retrieval Systems[J]. International Journal of Geographical Information Science, 2012, 26(4): 579-597.
[9]  LEACOCK C C. Milling in a Sparse Training Space for Word Sense Identification[EB/OL]. [2009-02-25]. http: //arxiv.org /PS_cache/cmp-lg/pdf/9511/9511007v1.pdf.
[10]  JIAN C L, HUANG M L. Research on Geographic Information Database Incremental Updating Method[C]//Proceedings of International Conference on Audio Language and Image Processing. Shanghai: [s.n.], 2010: 985-989.
[11]  WU Jianhua, FU Zhongliang. Methodology of Feature Change Detection and Matching in Data Updating[J]. Computer Applications, 2008, 28(6): 1612-1615. (吴建华, 付仲良. 数据更新中要素变化检测与匹配方法[J]. 计算机应用, 2008, 28(6): 1612-1615.)
[12]  YING Shen, LI Lin, LIU Wanzeng, et al. Change-only Updating Based on Object Matching in Version Databases[J]. Geomatics and Information Science of Wuhan University, 2009, 34(6): 752-755. (应申,李霖,刘万增,等. 版本数据库中基于目标匹配的变化信息提取与数据更新[J]. 武汉大学学报: 信息科学版,2009,34(6):752-755.)
[13]  ZHANG Feng, LIU Nan, LIU Renyi, et al. Research of Cadastral Data Modeling and Database Updating Based on Spatio-temporal Process[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(3): 303-309. (张丰,刘南,刘仁义,等. 面向对象的地籍时空过程表达与数据更新模型研究[J]. 测绘学报, 2010, 39(3): 303-309.
[14]  AI T H, CHENG X, LIU P, et al. A Shape Analysis and Template Matching of Building Features by the Fourier Transform Method[J]. Computers, Environment and Urban Systems, 2013, 41: 219-233.
[15]  KIELER B, HUANG W, HAUNERT J H, et al. Matching River Datasets of Different Scales[M]. Advances in GIScience. Berlin: Springer, 2009: 135-154.
[16]  DENG M, LI. Z L, CHEN. X Y. Extended Hausdorff Distance for Spatial Objects in GIS[J]. International Journal of Geographical Information Science, 2007, 21(4): 459-475.
[17]  DENG M, LI Z L. A Statistical Model for Directional Relations between Spatial Objects[J]. Geoinformatica, 2008, 12: 193-217.
[18]  PAN LI, WANG Hua. Automatic Recognition of Change Types of Residential Areas Using Topology Relations Model[J]. Geomatics and Information Science of Wuhan University, 2009, 34(3): 301-303. (潘励, 王华. 利用拓扑关系模型自动检测居民地的变化类型[J]. 武汉大学学报: 信息科学版, 2009, 34(3): 301-303.)
[19]  DENG M, CHENG T, CHEN X Y, et al. Multi-level Topological Relations between Spatial Regions Based upon Topological Invariants[J]. Geoinformatica, 2007, 11: 239-267.
[20]  TONG Xiaohua, DENG Susu, SHI Wenzhong. A Probabilistic Theory-based Matching Method[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(2): 210-217. (童小华, 邓愫愫, 史文中. 基于概率的地图实体匹配方法[J]. 测绘学报, 2007, 36(2): 210-217.)
[21]  WALTER V, FRITSCH D. Matching Spatial Data Sets: A Statistical Approach[J]. International Journal of Geograph-ical Information Systems, 1999, 13(5): 445-473.
[22]  ZHANG Liping, GUO Qingsheng, SUN Yan. The Method of Matching Residential Features in Topographic Maps at Neighboring Scales[J]. Geomatics and Information Science of Wuhan University, 2008, 33(6): 604-607. (章莉萍,郭庆胜,孙艳. 相邻比例尺地形图之间居民地要素匹配方法研究[J]. 武汉大学学报: 信息科学版, 2008, 33(6): 604-607.)

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